Cancer is a disease that continues to kill a tremendous number of people each year and there are a significant number of health professionals that handle various aspects of cancer and its treatment. Currently, when cancer is suspected, medical information about the tissue, such as a medical image, may be gathered for the affected tissue, where a physician reviews the medical information to identify possible areas in the tissue that may have cancer cells. This analysis typically leads to an all clear diagnosis (if no areas are identified by the physician) or a recommendation for a biopsy of the tissue to confirm that any possible areas of cancer cells are in fact cancerous cells. In the context of breast cancer, the medical image is typically a mammogram. This existing approach results in an about 60% cumulative risk of a false positive and an about 20% average false negative rate. A false positive may result in a patient who did not have cancer having to endure a painful, intrusive, and unnecessary biopsy. A false negative may result in not detecting cancer as early as it could have otherwise been detected.
Other systems exist that use computer-aided detection to assist a physician in analyzing medical images. However, many of these computer-aided detection systems actually reduce the accuracy of the analysis of the medical imaging thus resulting in higher number of false positives and false negatives. There remains a need for improved cancer detection and quantification systems and methods.